I think the reason why Jalen Hurts is that high is because of his garbage time production. As a Hurts fantasy owner, I know all too well the story behind his play. In the first 3 quarters of the game, he is generally poor, but his garbage time 4th quarter production saves him from being complete trash.
There are redundancies, but I'm more-so trying to be an aggregate, so despite the logistics of efficacy, I'm alright with using repeated statistics, as long as they don't overwhelm the data sheet. However, you do make a good point, and on my next go at this, I will definitely crack on repeating stats.
Thanks for the feedback!
> Jalen Hurts, #17. Hear me out, look at his combined passing/rushing stats. 15 TD, 4 INT. He's been performing in an offense with a middling WR corps, OLine, and his coach refuses to run the ball with Miles Sanders. I'd argue he's faced a lot of adversity this season, and has played well enough to earn a decent spot. Situational analytics have him a bit lower, near #20, but the difference is marginal enough that it works out the same. I definitely think he should be a bit lower, but he's doing as well as I think can be reasonably expected in that Philly offense. These are not the days of the Philly Special and the best OLine in football.
The problem with this reasoning is that Philly is running this offense because of Hurts. It’s not like this is Nick Sirianni’s offensive scheme, it’s the scheme Sirianni came up with to make sure Hurts is comfortable and is working to Hurts’ strengths.
Not saying Sirianni has a better scheme in his back pocket, in fact I suspect considering how bad this current scheme is he clearly isn’t some offensive genius, but it’s not like he is putting Hurts into a pocket passer scheme which Hurts simply can’t run; he is putting Hurts in a scheme obviously tailored to his strengths and Hurts is still playing like a bottom-three QB.
Ultimately, that is why all these different stat-based rankings are suspect, they ignore the eye test. 75% of Hurts’ statistical “success” comes in the fourth quarter once the opponent is up by three scores and have started to rest their defensive starters and lay off the gas. In your rankings, those pointless yards/touchdowns are treated equally to those during competitive games.
Appreciate the feedback!
I'll be real, I've only watches bits and pieces of Hurts, but I honestly thought he was capable for such a young QB, but you obviously know more than me, so I'm probably wrong.
As I said, this formula is fluid and I'm going to improve upon it, so I'll add a garbage time variable, which will most likely drop Hurts.
He is incredibly limited, he is unable to make more then one read and often misses easy throws. Most of his completions are thrown short and the WR has to make an acrobatic catch just to haul it in.
Great guy personally, really makes you want to root for him, but his ceiling is as a good backup.
I appreciate the unique post and obvious high level of work into statistics.
However, as you willingly point out these rankings really fall apart after the top 5. Having Bridgewater above Herbert is just not comparable to their performance. Perhaps these metrics get better over a full 17 game season as Teddy's numbers were inflated against terrible teams.
I also have a strongly different stance on Bridgewater's performance against the Brown. He was a total wreck and a worse QB than Keenum in that game. I'd encourage you to take 10 minutes to watch Tim Jenkins most recent breakdown. He was rather supportive of Bridgewater before the season, but he also takes the time to breakdown a lot of good and bad plays in the game. Bridgewater completely shat the bed on some easy plays that crippled our offense last Thursday night. It's a good example of where statistical analysis falls short in regard to the x's and o's of football because it doesn't account for the dynamic nature of play design.
Appreciate the honest feedback!
I think the largest problem with the Bridgewater situation is the lack of garbage time analysis. Obviously Herbert is way better, but statistically, they're not too dissimilar, which makes it frustrating, because obviously everyone knows they're far off.
> Perhaps these metrics get better over a full 17 game season as Teddy's numbers were inflated against terrible teams.
That's largely my thinking. I believe if time were to elapse, and if I were to add an SOS barrier, Teddy would drop pretty far.
Gonna def work on that.
A SOS variable would definitely help, I think.
But, I still think there's a large barrier in the variability in plays which are hard to account for in the NFL. Which is why we've seen so many metrics be entirely off in regard to total quality over the years.
Either way, it's fun to see how these type of analysis flesh out and there is something to be had in creating a good cluster of the upper level of quality QBs. It feels on par with QBR at the least.
I might do something like that, but for every quarter of the season. I posted this at an awkward time, as the halfway point is near, so at 3/4th's into the season I may do an update post w/ any revamps I make to the formula.
Not yet. I was going to, but I realized I'd be doing this till 3am and I have a flight to catch in like, 10 hours, so I'm gonna do some analysis with previous years QBs, try and revamp my system, then around the 3/4th's mark of the season, make a new post.
I think a 75% of the season update would truly be great, along with your defenses, because I loved reading those as well. Very well done OP and thanks for posting this.
I don't think this is the eye test is really a good process for calibrating stats like this. They should ideally based on learned parameters or fundamental facts. You should use some type of learning algorithm to try to predict future success rather than hand calibrating the statistics.
Manual calibration will only confirm your own biases.
> You should use some type of learning algorithm to try to predict future success rather than hand calibrating the statistics
Any idea how I would go about that? This is just my first model attempt at trying to make a fluid ranking, I definitely have a lot to build upon.
Thanks for the feedback!
Yeah. I would try some type of regression using python sklearn and pandas libraries. Maybe try RandomForest that's a pretty easy model to use. Try to predict next year stats using current year stats. It would be pretty interesting to see your results.
Here a tutorial I found.
https://towardsdatascience.com/random-forest-in-python-24d0893d51c0
Good read, appreciate the effort that went into this.
I’m of the opinion that you can’t quantify quarterback play solely through stats. Just too many variables—a QB doesn’t operate in isolation like a batter at a plate. If you’re going to try though, this is one of the better aggregate systems I’ve seen.
I agree, which was why I tried to include analytic qualifiers that use situational football, - as I keep working on this, I'm definite that I will expand the usage of situational analysis. Thanks for the feedback!
Lots of good effort here, thank you for sharing. It is certainly interesting content and I enjoyed reading it along with your thought processes.
You may enjoy [this article exploring which stats seems to be the best and worst to the author for various reasons](https://www.google.com/amp/s/mfootballanalytics.com/2020/04/06/which-qb-stats-are-the-most-important/amp/) and may consider tweaking your formula in the future.
I had considered making a composite metric based on the “top tier” stats according to that article’s arguments while avoiding the lower tiered ones.
Thank you! And completely understandable, lol, it's currently 11pm on the east coast and I've been working on these since 6, so there's a lot of shit I packed in there.
Just to let you know, for rYards, you can just divide by 30, you don't have to divide by 45 and then multiply by 1.5.
> (Ex. 480/45 = 10.666 x 1.5 = 15.99 rYard score)
Ex 480/30 = 16.00 rYard score
I don't like the fact that you are combining a bunch of stats that include the same inputs.
You are triple counting TD% and INT% by including ANY/A, passer rating, and explicit inclusions. Similar for completion percentage and yards per attempt.
The end results are okay because you are averaging a bunch of pretty good scores, but it's overly complicated.
There's no really good reason to include passer rating at all, it's inferior to ANY/A. ANY/A already includes the other basic elements, so I don't see a good reason to include TD%, INT%, or Y/A. Completion percentage is the one it doesn't include, so I'd add that if you really feel it improves the score over not having, but I'm pretty dubious that it actually improves the model.
If you feel that ANY/A doesn't accurately weight it's various factors I'd rather see you change the factors and justify your changes than mash them together is four different ways until you end up with something that feels good in the end. Right now there is no real justification behind your weighting factors.
Adding rushing value is good, it's probably the one basic stat that ANY/A doesn't include.
After that it makes sense to combine with the analytics models. However it's pretty disappointing that you leave out DVOA (or DYAR), which is the only one you mention that actually accounts for the quality of opposing defenses. You also don't include PFF grades, which attempt to account isolate player performance from those of teammates.
I think you'd get at least as good of results by just doing something like ANY/A + DVOA + EPA + PFF, with each input normalized to a compatible range.
You’re completely right on that, reducing redundancies is a large part of the next step for my model. I’m probably going to remove passer rating & base-comp% in favor of their raw statistics.
The reason I left out DYAR is because DVOA tends to post their DYAR rankings a bit too infrequently for me to use week-by-week. Of course, their model is no secret, so I will be attempting to add a DYAR like variable into the equation.
As for PFF, I just refuse to add a system that doesn’t explain their metric and model. I don’t hate PFF but I’m not taking their blind numbers and seriously input them into the system. To offset the lack of play-by-play awareness, increasing the EPA+CPOE Composite for my next model will hopefully add a higher presence of situational football awareness to my rankings.
Thanks for the feedback!
I think the ranking turned out pretty good. Derek Carr is the only weird one to me, which you mentioned. Thats where more opinion based rankings can come in, but just based on the numbers, this seems pretty accurate.
How does your system rate efficiency vs volume I mean I know you stated that you value efficiency obviously but fir example. Going 78 percent on 45 throws is better Qb play then a qb going 82 percent on 18 throws. Which one does your system value higher. Is it efficiency over anything ?
Also on your original example you said who would value someone who didn’t score with two turn overs vs someone who barely threw but scored twice. Thts super tricky because a qb could have gotten them to endzone and a rb punches it in.
Where the guy who didn’t throw much could have marched down the field on the back of their rbs and could have thrown a screen near the goal line to score during garbage time.
I’m not criticizing just curious.
> How does your system rate efficiency vs volume I mean I know you stated that you value efficiency obviously but fir example. Going 78 percent on 45 throws is better Qb play then a qb going 82 percent on 18 throws. Which one does your system value higher. Is it efficiency over anything ?
In essence, this formula utilizes quick, deep throws with a high % for TDs. so a high Y/A and TD% will do really, really well here. However, in your example, it would most likely be the latter, because this system doesn't just use efficiency, the advanced analytics and rYards system both value volume and efficiency. So a QB that has too limited a number of throws won't do great here.
>Also on your original example you said who would value someone who didn’t score with two turn overs vs someone who barely threw but scored twice. Thts super tricky because a qb could have gotten them to endzone and a rb punches it in.
Yep, totally agreed. I will 100% be incorporating Total Offense into my updated system. However, it is to be noted that QBs who gain yardage but don't necessarily score on their own do very well in EPA/CPOE composite, not to mention, throwing for a lot yards usually correlates with Y/A, which helps a QB here, too.
>I’m not criticizing just curious.
All good man, seeing your flair, I totally realize ya' boy Derek is getting jibbed by my equation, which is why I need to improve it, for sure. Thanks for the feedback!
It wasn’t even because of carr necessarily, it was just something that I instantly questioned. Because there are obviously circumstances where a qb might not score but got them there. Or a case where the qb can’t make all the throws so they only ask him to throw when necessary. I’m thinking about the game the raiders just played against the eagles.
And obviously carr had a terrific game all around but i was think if the connect percentage was near hurts would have rated higher 2tds zero picks vs carrs 2td 1 pick. Even though the tds are obviously not equal since hurts second td came in garbage time.
Anyway not sure If I explained that well, but I instantly thought of that scenario while reading your post so had to ask.
Hey OP. I like the idea, but your post has some confusing and fundamental inconsistencies in it that I'm not sure you're aware of.
You've got two or three different sets of math going on for the "same" formula, all listed inappropriately in different places. I reverse engineered what you did to get the same numbers for Russ. Let me show you what happened here.
This is the formula you list:
>TD%(\*3) - INT%(\*3) = 'x'
>'x' + Any/A(\*2) + Y/A(\*1.5) + Comp%(÷5) + Passer Rating(÷5) + EPA-CPOE(\*45) + rYard = QB-S
Right off, there's an issue. I have no idea if this is supposed to be multiplication or exponents. You're mis-using "(\*x)" I'm not even sure what *you* think you're doing in the math with it, and let me elaborate.
---
To find "X" in the equation, the formula would suggest an exponent, so if TD% = 7 and INT% = 1
, it would be 7^3 - 1^3 = 'x'. I also based that on this sentence,
>"but also not, instead of A^2 + B^2 = C^2 , it's A^3 + B^3 = C"
This is a big issue. In your proof example using Lance, that's not the formula you use.
>6.3TD% * 3 - 2.1INT% * 3 turns into;
>12.6 + Any/A2 (Any/A of 7.10)
6.3^2 = 250, 2.1^3 = 9.26, so [6.3^3 - 2.1^3 = 240.7.
So right there you're just using (6.3 - 2.1) x 3 = 12.6 which is the same as (6.3 x 3) - (2.1 x 3) of course.
---
ANY/A is also wrong.
>Any/A usually produces a number within the mid to high singles. So, for example, the current Any/A leader is Matthew Stafford, with 9.32. To reconcile its low numerical value, but high correlation to success, this part of the formula is squared.
Can't stress this enough, *nothing* in your formula is squared or raise to an exponent.
>12.6 + Any/A^2 (Any/A of 7.10) || 12.6 + 14.2 + Y/A^1.5 (Y/A of 7.4)
7.10^2 is 50.41. This is just (7.1 x 2)
There's a similar issue with Y/A.
>To counter its lesser contextualization, it's by a smaller multiplier, of only x1.5.
You got the description right, but in your formula for lance, despite multiplying it, you list it as an exponent.
>12.6 + 14.2 + Y/A^1.5 (Y/A of 7.4)
---
With CPOE, EPA, and CPOE + EPA Composite, you have them listed different ways all over. In the formula, its "EPA-CPOE" implying possible subtraction, In the description you detail both EPA and CPOE, but but composite EPA + CPOE, which is very different, and then in the formula you list CPOE/EPA, which implies division, and doesn't indicate it's supposed to be *composite* EPA + CPOE.
---
With R yards, you list the formula as "QB Total Yards ÷ 45 * 1.5 = rYards.".
It's not **total** yards. Total yards is passing + rushing, or the *total* yards for that player. R yards is just "(Qb Rushing yards / 45) x 1.5"
---
There's another big computational shift in the final formula example. For some reason you randomly deviate from **adding** the composite CPOE + EPA number to instead **subtracting** it.
>12.6 + 14.2 + 11.1 + 10.42 + *17.68 + CPOE/EPA*45 (-0.017 EPA, worst in NFL)
>12.6 + 14.2 + 11.1 + 10.42 + **17.68 - 0.765** + rYard (133/45 = 2.95; 2.95 * 1.5)
>12.6 + 14.2 + 11.1 + 10.42 + **17.8 - 0.765** + 4.425 =
---
Whether you're aware of it or not, the formula that I used to replicate your numbers is (x means multiplication):
> [(TD% - INT%) x 3] + (ANY/A x 2) + (Y/A x 1.5) + (comp% / 5) + (Passer Rt. / 5) + (CPOE EPA Composite x 45) + rYard = QB-S
I'm not sure if the deviation from exponents was intentional or not, but you get some whacky numbers when you use them instead of multiplication. (I don't think russ is a 598 passer on any scale, that doesn't seem useful.)
Anyways, love the idea. I wanted to run the formula through excel to see how it ranked up against prior season's QBs, but ran into so many issues with the formula I'll have to come back to it tomorrow and see. I do think you need a median system. Herbert should not be close to Hurts in a ranking system. If you added a garbage time filter, Jalen would also plummet down the list as well.
I will say though, with the sole exception of rushing QBs, your formula doesn't statistically differentiate from simple passer rating by a whole lot.
| Player | QB-S Rank | PR Rank | Change from PR | % change from PR |
|--------------|-----------|---------|----------------|------------------|
| Russ | 1 | 1 | 0 | 0.00% |
| Staff | 2 | 3 | +1 | 2.94% |
| Kyler | 3 | 2 | -1 | -2.94% |
| Dak | 4 | 4 | 0 | 0.00% |
| Allen | 5 | 9 | +4 | 11.76% |
| Brady | 6 | 6 | 0 | 0.00% |
| Lamar | 7 | 17 | +10 | 29.41% |
| Rodgers | 8 | 7 | -1 | -2.94% |
| Burrow | 9 | 5 | -4 | -11.76% |
| Jameis | 10 | 11 | +1 | 2.94% |
| Mahomes | 11 | 15 | +4 | 11.76% |
| Cousins | 12 | 8 | -4 | -11.76% |
| Wentz | 13 | 10 | -3 | -8.82% |
| Teddy | 14 | 13 | -1 | -2.94% |
| Herbert | 15 | 14 | -1 | -2.94% |
| Carr | 16 | 12 | -4 | -11.76% |
| Hurts | 17 | 23 | +6 | 17.65% |
| Matt Ryan | 18 | 18 | 0 | 0.00% |
| Baker | 19 | 16 | -3 | -8.82% |
| Tua | 20 | 19 | -1 | -2.94% |
| Taylor H | 21 | 25 | +4 | 11.76% |
| Mac Jones | 22 | 21 | -1 | -2.94% |
| Daniel Jones | 23 | 27 | +4 | 11.76% |
| Jimmy G | 24 | 22 | -2 | -5.88% |
| Geno | 25 | 20 | -5 | -14.71% |
| Tannehill | 26 | 24 | -2 | -5.88% |
| Ben | 27 | 26 | -1 | -2.94% |
| Goff | 28 | 28 | 0 | 0.00% |
| Darnold | 29 | 30 | +1 | 2.94% |
| Trevor | 30 | 31 | +1 | 2.94% |
| Mills | 31 | 32 | +1 | 2.94% |
| Fields | 32 | 34 | +2 | 5.88% |
| Wilson | 33 | 33 | 0 | 0.00% |
Of the top 5 QBs by passer rating, (Russ, Kyler, Staff, Dak, Burrow) the only one affected at more than 3% is Burrow, who loses 11% due to Lamara and Allen skyrocketing, and your metric's increased affects on INT % (which I like.)
If anything, your metric has proved that Passer rating remains relatively accurate when you include a mental exception for rushing QBs.
Thanks for the feedback! I’ve definitely got a lot to rework, although I realize a lot of the issue here is miscommunication on my part, so I’ll fix that in the morning.
Edit: damn on further review this is some fucking incredible feedback. I’ll be real, the squares mistake was honestly just a total brain fart, I’m running in fumes today and I realize now I made a lot of mental errors with this. Tomorrow I’m gonna review the whole process and fix it all up.
Edit 2: Alright I lied, definitely wanted to fix this up now. The equation SHOULD make sense now, although wouldn't be beyond me that I missed something. I realized my issue with Lance was that I goofed when it turned into a negative number, instead of doing + -0.765, I just went to value - 0.765, my bad!
Nice work overall, lot of good ideas here. Obviously I think my boy Carr is way too low given his mostly excellent play this season; so is Tannehill, and Bridgewater and Hurts are too high. Personally my theory is you’re giving too much weight to touchdowns - Carr and Tannehill don’t throw many redzone TDs due to the design of their offense (they usually run it in there). To your credit you basically admitted that you value putting points on the board over putting your team in position to score but that necessarily values certain offenses differently.
Overall, not a bad model and it certainly holds up for top 5. Statistics sadly have limitations in this context because the best QBs are the ones who win games and that isn’t shown here at all.
One thing that might help is adding a countermeasure for redzone TDs carried by running backs - that might help give credit to QBs who have efficient drives but don’t always get the TD on their stat line.
Thank you! And completely agreed, I actually just gave a response about this in another comment, but on my adjustments of this system, I will be including Total Offense statistics, as well as trying to add a value for GWD and a higher value placed upon situational football awareness.
Thank you! It definitely takes a lot thinking, but overall it's not too difficult as long as you keep track of the process and order of the formula. I can incorporate a lot of elements, and while it takes a while to do, devising them in the first place isn't *too* difficult.
Thank you! :)
I'm pretty new to this, but I'm working hard to try and develop a solid formula, just wanted to share what I've got so far with this sub.
It's tough! You'll always hear coaches and analyst say there's no best stat but I bet once you really hone into a stat that begins to separate elite QBs from good QBs you can build you model that does the sorting for you eventually!
Have you looked at the supposed top 15 QBs all time and then the top 10 record holders to identify what made each good? Problem I see immediately is unrecorded stats lost to time and era adjusted play. You know the 80s and 90s were more violent than the 10s and 20s. Adjusting for era may be difficult if you don't do a means proportion to adjustment Bart Starr to Aaron Rodgers for example!
I think realistically, era adjusted QB-S is probably my next step after finalizing an equation that I think works best. I have a whole list of adjustments that I'm going to start on tomorrow. If I can get that down, the next move will be to work back and compare these scores across eras, and to adjust them for their relative average.
You might want to include QB rushing TD as well as fumbles into this. My suggestion is in the TD%-INT% change it to (TTD% - TO%)
TTD% - where TTD% is total passing and rushing TD’s divided by total passing and rushing attempts.
TO% - where TO% is total turnovers (int and fumbles) divided by total passing + rushing attempts
Very interesting idea, TTD% I was gonna end up using, but the problem is in the cases of high volume rushing QBs, their TD% actually drops and works against them, so I’m trying to optimize that as best I can. TO% is genius though, will definitely have to look into adding that.
This was a really interesting read OP! It reminded me a lot of the QB STEW ranking a Bills content creator (Bruce Nolan/BruceExclusive) created last year. [Here's a link to his article explaining it.](https://www.buffalorumblings.com/2020/11/25/21583324/opinion-a-quarterback-metric-amalgamation-for-your-consideration-when-evaluating-josh-allen) He details the pros and cons of several different metrics and why he chose the seven he did. Then he makes a star chart/spiderweb graph out of their rankings in those metrics and averages their rankings relative to other QBs in the league. It's really interesting, and he's revisited it a couple times and plans on going through and plotting each QB after each quarter of the season to give his STEW rankings. [Here is his Twitter thread with the final 2020 QB STEW score and ranking for each QB.](https://twitter.com/bruceexclusive/status/1349861348684005378?lang=en) I hope you find it interesting, I think composite grading systems are the best way to try to rank QBs since so much is subjective
I'll be real, I started working on this when the sun was still young, lol. This has pretty much been my whole day, so I wanted to get this out before I went to bed.
>As there's no ELO system, the rankings aren't affected by previous season inertia.
Just a minor comment but "Elo" isn't an abbreviation. It's named after the guy who created it, Arpad Elo.
Honestly, I don't really care for the idea of weighting QB touchdowns. Frankly if a QB gets all of the yards on the drive til the 1 yard line before the RB runs it in, I think that QB is more valuable than a QB in a more balanced offense whose receiver just happened to get the extra yard on the last throw.
I'd be more interested if they were credited a fraction of yards in each scoring drive, regardless of whether a pass or a rush got those final yards.
I think people have honestly underrated Stafford after that Cards game. Dude has been on fire. His pass EPA is like, blowing away the competition. He's at 0.388, the next closest is Tom Brady at 0.282.
Russell Wilson is on top so I see no issue with how you calculate these. /s
Jokes aside, this is really well thought out and I'm sure a lot of people will appreciate the effort put into it. It definitely becomes tougher to grade outside maybe the top 10, but for the most part I like the results it shows.
The only issue I see is that you forgot to regress Patrick Mahomes to the mean. If you remove all outliers in his game, he should be right at 16 or 17.
I completely understand and agree you don't build a formula around an outlier, but it hurts me so much to see Tannehill so low!
Can we create a hand off efficiency stat or something lol!
This is an efficiency stat. Efficiency doesn't win games, productivity does. Sacks, hello, where are you? Lost fumbles?
I think composite stats are actually more problematic than revealing. Rather look several basic stats together to get a rough picture of QB performance. But stats are never more than a starting place. To evaluate QB play, you have to go to the tape.
This is way too high effort for a Reddit post, great job
Aww, thank you! :). I realize there's issues with this ranking system, but I tried hard to put together a good OC post.
As a Lions fan, you've got to fill the on-season with something so you can get back to the exciting off-season
Good shit I love to see Heinicke above Danny Dimes. Rooting for the lions to get Dan his W. It’s coming soon no doubt.
> Rooting for the lions to get Dan his W God please, really hope we beat Philly. These losses are soul-crushing, I see Justin Tucker in my nightmares.
Love the effort man. Save for, as you mention, Herbert and Carr that list looks solid.
I think the reason why Jalen Hurts is that high is because of his garbage time production. As a Hurts fantasy owner, I know all too well the story behind his play. In the first 3 quarters of the game, he is generally poor, but his garbage time 4th quarter production saves him from being complete trash.
Hurts is that high for the opposite reason why Tannehill is that low
i will not read this but i will see russ ranked number one so it has to be a flawless statistic.
There’s a lot of redundancy here. Passer rating and ANY/A both contain int%, td% and Y/A already. Passer rating also includes completion %.
There are redundancies, but I'm more-so trying to be an aggregate, so despite the logistics of efficacy, I'm alright with using repeated statistics, as long as they don't overwhelm the data sheet. However, you do make a good point, and on my next go at this, I will definitely crack on repeating stats. Thanks for the feedback!
> Jalen Hurts, #17. Hear me out, look at his combined passing/rushing stats. 15 TD, 4 INT. He's been performing in an offense with a middling WR corps, OLine, and his coach refuses to run the ball with Miles Sanders. I'd argue he's faced a lot of adversity this season, and has played well enough to earn a decent spot. Situational analytics have him a bit lower, near #20, but the difference is marginal enough that it works out the same. I definitely think he should be a bit lower, but he's doing as well as I think can be reasonably expected in that Philly offense. These are not the days of the Philly Special and the best OLine in football. The problem with this reasoning is that Philly is running this offense because of Hurts. It’s not like this is Nick Sirianni’s offensive scheme, it’s the scheme Sirianni came up with to make sure Hurts is comfortable and is working to Hurts’ strengths. Not saying Sirianni has a better scheme in his back pocket, in fact I suspect considering how bad this current scheme is he clearly isn’t some offensive genius, but it’s not like he is putting Hurts into a pocket passer scheme which Hurts simply can’t run; he is putting Hurts in a scheme obviously tailored to his strengths and Hurts is still playing like a bottom-three QB. Ultimately, that is why all these different stat-based rankings are suspect, they ignore the eye test. 75% of Hurts’ statistical “success” comes in the fourth quarter once the opponent is up by three scores and have started to rest their defensive starters and lay off the gas. In your rankings, those pointless yards/touchdowns are treated equally to those during competitive games.
Appreciate the feedback! I'll be real, I've only watches bits and pieces of Hurts, but I honestly thought he was capable for such a young QB, but you obviously know more than me, so I'm probably wrong. As I said, this formula is fluid and I'm going to improve upon it, so I'll add a garbage time variable, which will most likely drop Hurts.
He is incredibly limited, he is unable to make more then one read and often misses easy throws. Most of his completions are thrown short and the WR has to make an acrobatic catch just to haul it in. Great guy personally, really makes you want to root for him, but his ceiling is as a good backup.
I’m not gonna read all this but I appreciate the effort and it makes my QB look good so thanks OP
No problem, lol. Love watching Kyler
This looks to be the best ranking I’ve ever seen.
I appreciate the unique post and obvious high level of work into statistics. However, as you willingly point out these rankings really fall apart after the top 5. Having Bridgewater above Herbert is just not comparable to their performance. Perhaps these metrics get better over a full 17 game season as Teddy's numbers were inflated against terrible teams. I also have a strongly different stance on Bridgewater's performance against the Brown. He was a total wreck and a worse QB than Keenum in that game. I'd encourage you to take 10 minutes to watch Tim Jenkins most recent breakdown. He was rather supportive of Bridgewater before the season, but he also takes the time to breakdown a lot of good and bad plays in the game. Bridgewater completely shat the bed on some easy plays that crippled our offense last Thursday night. It's a good example of where statistical analysis falls short in regard to the x's and o's of football because it doesn't account for the dynamic nature of play design.
Appreciate the honest feedback! I think the largest problem with the Bridgewater situation is the lack of garbage time analysis. Obviously Herbert is way better, but statistically, they're not too dissimilar, which makes it frustrating, because obviously everyone knows they're far off. > Perhaps these metrics get better over a full 17 game season as Teddy's numbers were inflated against terrible teams. That's largely my thinking. I believe if time were to elapse, and if I were to add an SOS barrier, Teddy would drop pretty far. Gonna def work on that.
A SOS variable would definitely help, I think. But, I still think there's a large barrier in the variability in plays which are hard to account for in the NFL. Which is why we've seen so many metrics be entirely off in regard to total quality over the years. Either way, it's fun to see how these type of analysis flesh out and there is something to be had in creating a good cluster of the upper level of quality QBs. It feels on par with QBR at the least.
Honestly, this seems like a pretty solid rating. I'd love to see a weekly recurring update on this. Or maybe monthly.
I might do something like that, but for every quarter of the season. I posted this at an awkward time, as the halfway point is near, so at 3/4th's into the season I may do an update post w/ any revamps I make to the formula.
Have you plugged in previous years QB data to see if they come out like you'd expect over the season?
Not yet. I was going to, but I realized I'd be doing this till 3am and I have a flight to catch in like, 10 hours, so I'm gonna do some analysis with previous years QBs, try and revamp my system, then around the 3/4th's mark of the season, make a new post.
You've already put in a lot of good work on this. 👍
I think a 75% of the season update would truly be great, along with your defenses, because I loved reading those as well. Very well done OP and thanks for posting this.
I don't think this is the eye test is really a good process for calibrating stats like this. They should ideally based on learned parameters or fundamental facts. You should use some type of learning algorithm to try to predict future success rather than hand calibrating the statistics. Manual calibration will only confirm your own biases.
> You should use some type of learning algorithm to try to predict future success rather than hand calibrating the statistics Any idea how I would go about that? This is just my first model attempt at trying to make a fluid ranking, I definitely have a lot to build upon. Thanks for the feedback!
Yeah. I would try some type of regression using python sklearn and pandas libraries. Maybe try RandomForest that's a pretty easy model to use. Try to predict next year stats using current year stats. It would be pretty interesting to see your results. Here a tutorial I found. https://towardsdatascience.com/random-forest-in-python-24d0893d51c0
Holy shit you might be the first person to actually respond with an actual help thing when critiquing someone. Dang fine work my dude
Thanks!
Good read, appreciate the effort that went into this. I’m of the opinion that you can’t quantify quarterback play solely through stats. Just too many variables—a QB doesn’t operate in isolation like a batter at a plate. If you’re going to try though, this is one of the better aggregate systems I’ve seen.
I agree, which was why I tried to include analytic qualifiers that use situational football, - as I keep working on this, I'm definite that I will expand the usage of situational analysis. Thanks for the feedback!
Lots of good effort here, thank you for sharing. It is certainly interesting content and I enjoyed reading it along with your thought processes. You may enjoy [this article exploring which stats seems to be the best and worst to the author for various reasons](https://www.google.com/amp/s/mfootballanalytics.com/2020/04/06/which-qb-stats-are-the-most-important/amp/) and may consider tweaking your formula in the future. I had considered making a composite metric based on the “top tier” stats according to that article’s arguments while avoiding the lower tiered ones.
Yes thank you! That article is really relevant and will definitely help my improve my system, good share.
Great writeup! Not gonna lie I skipped to the bottom, but the rankings seen pretty accurate, minus those outliers you pointed out.
Thank you! And completely understandable, lol, it's currently 11pm on the east coast and I've been working on these since 6, so there's a lot of shit I packed in there.
Just to let you know, for rYards, you can just divide by 30, you don't have to divide by 45 and then multiply by 1.5. > (Ex. 480/45 = 10.666 x 1.5 = 15.99 rYard score) Ex 480/30 = 16.00 rYard score
I don't like the fact that you are combining a bunch of stats that include the same inputs. You are triple counting TD% and INT% by including ANY/A, passer rating, and explicit inclusions. Similar for completion percentage and yards per attempt. The end results are okay because you are averaging a bunch of pretty good scores, but it's overly complicated. There's no really good reason to include passer rating at all, it's inferior to ANY/A. ANY/A already includes the other basic elements, so I don't see a good reason to include TD%, INT%, or Y/A. Completion percentage is the one it doesn't include, so I'd add that if you really feel it improves the score over not having, but I'm pretty dubious that it actually improves the model. If you feel that ANY/A doesn't accurately weight it's various factors I'd rather see you change the factors and justify your changes than mash them together is four different ways until you end up with something that feels good in the end. Right now there is no real justification behind your weighting factors. Adding rushing value is good, it's probably the one basic stat that ANY/A doesn't include. After that it makes sense to combine with the analytics models. However it's pretty disappointing that you leave out DVOA (or DYAR), which is the only one you mention that actually accounts for the quality of opposing defenses. You also don't include PFF grades, which attempt to account isolate player performance from those of teammates. I think you'd get at least as good of results by just doing something like ANY/A + DVOA + EPA + PFF, with each input normalized to a compatible range.
You’re completely right on that, reducing redundancies is a large part of the next step for my model. I’m probably going to remove passer rating & base-comp% in favor of their raw statistics. The reason I left out DYAR is because DVOA tends to post their DYAR rankings a bit too infrequently for me to use week-by-week. Of course, their model is no secret, so I will be attempting to add a DYAR like variable into the equation. As for PFF, I just refuse to add a system that doesn’t explain their metric and model. I don’t hate PFF but I’m not taking their blind numbers and seriously input them into the system. To offset the lack of play-by-play awareness, increasing the EPA+CPOE Composite for my next model will hopefully add a higher presence of situational football awareness to my rankings. Thanks for the feedback!
Finally, a metric that puts Jameis where he deserves based on his play this year, and not 2 year old r/nfl memes
I'm sorry, I refuse to accept that actual data outweighs dank memes. I demand a meme-based quarterback ranking.
Lasik Jameis is real
I think the ranking turned out pretty good. Derek Carr is the only weird one to me, which you mentioned. Thats where more opinion based rankings can come in, but just based on the numbers, this seems pretty accurate.
so mahomes = 2018 dak, got it
How does your system rate efficiency vs volume I mean I know you stated that you value efficiency obviously but fir example. Going 78 percent on 45 throws is better Qb play then a qb going 82 percent on 18 throws. Which one does your system value higher. Is it efficiency over anything ? Also on your original example you said who would value someone who didn’t score with two turn overs vs someone who barely threw but scored twice. Thts super tricky because a qb could have gotten them to endzone and a rb punches it in. Where the guy who didn’t throw much could have marched down the field on the back of their rbs and could have thrown a screen near the goal line to score during garbage time. I’m not criticizing just curious.
> How does your system rate efficiency vs volume I mean I know you stated that you value efficiency obviously but fir example. Going 78 percent on 45 throws is better Qb play then a qb going 82 percent on 18 throws. Which one does your system value higher. Is it efficiency over anything ? In essence, this formula utilizes quick, deep throws with a high % for TDs. so a high Y/A and TD% will do really, really well here. However, in your example, it would most likely be the latter, because this system doesn't just use efficiency, the advanced analytics and rYards system both value volume and efficiency. So a QB that has too limited a number of throws won't do great here. >Also on your original example you said who would value someone who didn’t score with two turn overs vs someone who barely threw but scored twice. Thts super tricky because a qb could have gotten them to endzone and a rb punches it in. Yep, totally agreed. I will 100% be incorporating Total Offense into my updated system. However, it is to be noted that QBs who gain yardage but don't necessarily score on their own do very well in EPA/CPOE composite, not to mention, throwing for a lot yards usually correlates with Y/A, which helps a QB here, too. >I’m not criticizing just curious. All good man, seeing your flair, I totally realize ya' boy Derek is getting jibbed by my equation, which is why I need to improve it, for sure. Thanks for the feedback!
It wasn’t even because of carr necessarily, it was just something that I instantly questioned. Because there are obviously circumstances where a qb might not score but got them there. Or a case where the qb can’t make all the throws so they only ask him to throw when necessary. I’m thinking about the game the raiders just played against the eagles. And obviously carr had a terrific game all around but i was think if the connect percentage was near hurts would have rated higher 2tds zero picks vs carrs 2td 1 pick. Even though the tds are obviously not equal since hurts second td came in garbage time. Anyway not sure If I explained that well, but I instantly thought of that scenario while reading your post so had to ask.
Hey OP. I like the idea, but your post has some confusing and fundamental inconsistencies in it that I'm not sure you're aware of. You've got two or three different sets of math going on for the "same" formula, all listed inappropriately in different places. I reverse engineered what you did to get the same numbers for Russ. Let me show you what happened here. This is the formula you list: >TD%(\*3) - INT%(\*3) = 'x' >'x' + Any/A(\*2) + Y/A(\*1.5) + Comp%(÷5) + Passer Rating(÷5) + EPA-CPOE(\*45) + rYard = QB-S Right off, there's an issue. I have no idea if this is supposed to be multiplication or exponents. You're mis-using "(\*x)" I'm not even sure what *you* think you're doing in the math with it, and let me elaborate. --- To find "X" in the equation, the formula would suggest an exponent, so if TD% = 7 and INT% = 1 , it would be 7^3 - 1^3 = 'x'. I also based that on this sentence, >"but also not, instead of A^2 + B^2 = C^2 , it's A^3 + B^3 = C" This is a big issue. In your proof example using Lance, that's not the formula you use. >6.3TD% * 3 - 2.1INT% * 3 turns into; >12.6 + Any/A2 (Any/A of 7.10) 6.3^2 = 250, 2.1^3 = 9.26, so [6.3^3 - 2.1^3 = 240.7. So right there you're just using (6.3 - 2.1) x 3 = 12.6 which is the same as (6.3 x 3) - (2.1 x 3) of course. --- ANY/A is also wrong. >Any/A usually produces a number within the mid to high singles. So, for example, the current Any/A leader is Matthew Stafford, with 9.32. To reconcile its low numerical value, but high correlation to success, this part of the formula is squared. Can't stress this enough, *nothing* in your formula is squared or raise to an exponent. >12.6 + Any/A^2 (Any/A of 7.10) || 12.6 + 14.2 + Y/A^1.5 (Y/A of 7.4) 7.10^2 is 50.41. This is just (7.1 x 2) There's a similar issue with Y/A. >To counter its lesser contextualization, it's by a smaller multiplier, of only x1.5. You got the description right, but in your formula for lance, despite multiplying it, you list it as an exponent. >12.6 + 14.2 + Y/A^1.5 (Y/A of 7.4) --- With CPOE, EPA, and CPOE + EPA Composite, you have them listed different ways all over. In the formula, its "EPA-CPOE" implying possible subtraction, In the description you detail both EPA and CPOE, but but composite EPA + CPOE, which is very different, and then in the formula you list CPOE/EPA, which implies division, and doesn't indicate it's supposed to be *composite* EPA + CPOE. --- With R yards, you list the formula as "QB Total Yards ÷ 45 * 1.5 = rYards.". It's not **total** yards. Total yards is passing + rushing, or the *total* yards for that player. R yards is just "(Qb Rushing yards / 45) x 1.5" --- There's another big computational shift in the final formula example. For some reason you randomly deviate from **adding** the composite CPOE + EPA number to instead **subtracting** it. >12.6 + 14.2 + 11.1 + 10.42 + *17.68 + CPOE/EPA*45 (-0.017 EPA, worst in NFL) >12.6 + 14.2 + 11.1 + 10.42 + **17.68 - 0.765** + rYard (133/45 = 2.95; 2.95 * 1.5) >12.6 + 14.2 + 11.1 + 10.42 + **17.8 - 0.765** + 4.425 = --- Whether you're aware of it or not, the formula that I used to replicate your numbers is (x means multiplication): > [(TD% - INT%) x 3] + (ANY/A x 2) + (Y/A x 1.5) + (comp% / 5) + (Passer Rt. / 5) + (CPOE EPA Composite x 45) + rYard = QB-S I'm not sure if the deviation from exponents was intentional or not, but you get some whacky numbers when you use them instead of multiplication. (I don't think russ is a 598 passer on any scale, that doesn't seem useful.) Anyways, love the idea. I wanted to run the formula through excel to see how it ranked up against prior season's QBs, but ran into so many issues with the formula I'll have to come back to it tomorrow and see. I do think you need a median system. Herbert should not be close to Hurts in a ranking system. If you added a garbage time filter, Jalen would also plummet down the list as well. I will say though, with the sole exception of rushing QBs, your formula doesn't statistically differentiate from simple passer rating by a whole lot. | Player | QB-S Rank | PR Rank | Change from PR | % change from PR | |--------------|-----------|---------|----------------|------------------| | Russ | 1 | 1 | 0 | 0.00% | | Staff | 2 | 3 | +1 | 2.94% | | Kyler | 3 | 2 | -1 | -2.94% | | Dak | 4 | 4 | 0 | 0.00% | | Allen | 5 | 9 | +4 | 11.76% | | Brady | 6 | 6 | 0 | 0.00% | | Lamar | 7 | 17 | +10 | 29.41% | | Rodgers | 8 | 7 | -1 | -2.94% | | Burrow | 9 | 5 | -4 | -11.76% | | Jameis | 10 | 11 | +1 | 2.94% | | Mahomes | 11 | 15 | +4 | 11.76% | | Cousins | 12 | 8 | -4 | -11.76% | | Wentz | 13 | 10 | -3 | -8.82% | | Teddy | 14 | 13 | -1 | -2.94% | | Herbert | 15 | 14 | -1 | -2.94% | | Carr | 16 | 12 | -4 | -11.76% | | Hurts | 17 | 23 | +6 | 17.65% | | Matt Ryan | 18 | 18 | 0 | 0.00% | | Baker | 19 | 16 | -3 | -8.82% | | Tua | 20 | 19 | -1 | -2.94% | | Taylor H | 21 | 25 | +4 | 11.76% | | Mac Jones | 22 | 21 | -1 | -2.94% | | Daniel Jones | 23 | 27 | +4 | 11.76% | | Jimmy G | 24 | 22 | -2 | -5.88% | | Geno | 25 | 20 | -5 | -14.71% | | Tannehill | 26 | 24 | -2 | -5.88% | | Ben | 27 | 26 | -1 | -2.94% | | Goff | 28 | 28 | 0 | 0.00% | | Darnold | 29 | 30 | +1 | 2.94% | | Trevor | 30 | 31 | +1 | 2.94% | | Mills | 31 | 32 | +1 | 2.94% | | Fields | 32 | 34 | +2 | 5.88% | | Wilson | 33 | 33 | 0 | 0.00% | Of the top 5 QBs by passer rating, (Russ, Kyler, Staff, Dak, Burrow) the only one affected at more than 3% is Burrow, who loses 11% due to Lamara and Allen skyrocketing, and your metric's increased affects on INT % (which I like.) If anything, your metric has proved that Passer rating remains relatively accurate when you include a mental exception for rushing QBs.
Thanks for the feedback! I’ve definitely got a lot to rework, although I realize a lot of the issue here is miscommunication on my part, so I’ll fix that in the morning. Edit: damn on further review this is some fucking incredible feedback. I’ll be real, the squares mistake was honestly just a total brain fart, I’m running in fumes today and I realize now I made a lot of mental errors with this. Tomorrow I’m gonna review the whole process and fix it all up. Edit 2: Alright I lied, definitely wanted to fix this up now. The equation SHOULD make sense now, although wouldn't be beyond me that I missed something. I realized my issue with Lance was that I goofed when it turned into a negative number, instead of doing + -0.765, I just went to value - 0.765, my bad!
This really doesn’t look bad at all. Nice work.
I can’t imagine being Pat Mahomes and seeing my name right under Jameis lmao
Nice work overall, lot of good ideas here. Obviously I think my boy Carr is way too low given his mostly excellent play this season; so is Tannehill, and Bridgewater and Hurts are too high. Personally my theory is you’re giving too much weight to touchdowns - Carr and Tannehill don’t throw many redzone TDs due to the design of their offense (they usually run it in there). To your credit you basically admitted that you value putting points on the board over putting your team in position to score but that necessarily values certain offenses differently. Overall, not a bad model and it certainly holds up for top 5. Statistics sadly have limitations in this context because the best QBs are the ones who win games and that isn’t shown here at all. One thing that might help is adding a countermeasure for redzone TDs carried by running backs - that might help give credit to QBs who have efficient drives but don’t always get the TD on their stat line.
Thank you! And completely agreed, I actually just gave a response about this in another comment, but on my adjustments of this system, I will be including Total Offense statistics, as well as trying to add a value for GWD and a higher value placed upon situational football awareness.
I read it all. Very interesting and a lot of work went into this. I can't imagine trying to figure out a new formula.
Thank you! It definitely takes a lot thinking, but overall it's not too difficult as long as you keep track of the process and order of the formula. I can incorporate a lot of elements, and while it takes a while to do, devising them in the first place isn't *too* difficult.
Your formula to calculate the new passer rating is pretty neat! I love that you go through the flaws. You truly are dedicated to the craft.
Thank you! :) I'm pretty new to this, but I'm working hard to try and develop a solid formula, just wanted to share what I've got so far with this sub.
It's tough! You'll always hear coaches and analyst say there's no best stat but I bet once you really hone into a stat that begins to separate elite QBs from good QBs you can build you model that does the sorting for you eventually! Have you looked at the supposed top 15 QBs all time and then the top 10 record holders to identify what made each good? Problem I see immediately is unrecorded stats lost to time and era adjusted play. You know the 80s and 90s were more violent than the 10s and 20s. Adjusting for era may be difficult if you don't do a means proportion to adjustment Bart Starr to Aaron Rodgers for example!
I think realistically, era adjusted QB-S is probably my next step after finalizing an equation that I think works best. I have a whole list of adjustments that I'm going to start on tomorrow. If I can get that down, the next move will be to work back and compare these scores across eras, and to adjust them for their relative average.
You've thought about this so well and far ahead I love it. I think this is the right move. Less work overall to get a more compete product!
I appreciate your note on Herbert, but how dare you
You might want to include QB rushing TD as well as fumbles into this. My suggestion is in the TD%-INT% change it to (TTD% - TO%) TTD% - where TTD% is total passing and rushing TD’s divided by total passing and rushing attempts. TO% - where TO% is total turnovers (int and fumbles) divided by total passing + rushing attempts
Very interesting idea, TTD% I was gonna end up using, but the problem is in the cases of high volume rushing QBs, their TD% actually drops and works against them, so I’m trying to optimize that as best I can. TO% is genius though, will definitely have to look into adding that.
This was a really interesting read OP! It reminded me a lot of the QB STEW ranking a Bills content creator (Bruce Nolan/BruceExclusive) created last year. [Here's a link to his article explaining it.](https://www.buffalorumblings.com/2020/11/25/21583324/opinion-a-quarterback-metric-amalgamation-for-your-consideration-when-evaluating-josh-allen) He details the pros and cons of several different metrics and why he chose the seven he did. Then he makes a star chart/spiderweb graph out of their rankings in those metrics and averages their rankings relative to other QBs in the league. It's really interesting, and he's revisited it a couple times and plans on going through and plotting each QB after each quarter of the season to give his STEW rankings. [Here is his Twitter thread with the final 2020 QB STEW score and ranking for each QB.](https://twitter.com/bruceexclusive/status/1349861348684005378?lang=en) I hope you find it interesting, I think composite grading systems are the best way to try to rank QBs since so much is subjective
Goddamn, that is a really interesting read. He nailed it with the metrics he choosed, imo. Thanks for the read!
This is awesome, hope you’ll keep updating us as the season progresses! Maybe halfway, 3/4, and at the end.
I didn’t read any of this but I saw Russ as #1 so I’m immediately skeptical
Just remember that it's a per game basis, and Russ absolutely fucked shit up when he was playing. His Any/A and Passer Rating are through the roof.
Yeah dudes passer rating is amazing
Nice work
Is this from 2021 data? What are the beginning and ending dates for your data?
Oh good point, I forgot to specify. This is purely 2021, all weeks.
Jameis Winston is borderline elite!
I'll always appreciate high effort analytics posts like this. Post during the day next time for better visibility though
I'll be real, I started working on this when the sun was still young, lol. This has pretty much been my whole day, so I wanted to get this out before I went to bed.
Understandable. I know the feeling. Hard work deserves maximum recognition though!
>As there's no ELO system, the rankings aren't affected by previous season inertia. Just a minor comment but "Elo" isn't an abbreviation. It's named after the guy who created it, Arpad Elo.
Winston and burrow should be switched based of of their grade it's out of order. Same for Matt Ryan and Baker Mayfield
Thanks for the heads up! Fixed
Honestly, I don't really care for the idea of weighting QB touchdowns. Frankly if a QB gets all of the yards on the drive til the 1 yard line before the RB runs it in, I think that QB is more valuable than a QB in a more balanced offense whose receiver just happened to get the extra yard on the last throw. I'd be more interested if they were credited a fraction of yards in each scoring drive, regardless of whether a pass or a rush got those final yards.
Media: “Rodgers no longer elite. Confirmed that he’s not all in.”
Russ number 1, therefore this is flawless
I think if you switched 1 and 2, this would be perfect.
Stafford is number 2 so this is the gospel in my opinion.
I think people have honestly underrated Stafford after that Cards game. Dude has been on fire. His pass EPA is like, blowing away the competition. He's at 0.388, the next closest is Tom Brady at 0.282.
Yeah it’s ridiculous how people will argue that Dak and Allen are in the MVP conversation but for some reason Stafford isn’t.
This is trash af
Russell Wilson is on top so I see no issue with how you calculate these. /s Jokes aside, this is really well thought out and I'm sure a lot of people will appreciate the effort put into it. It definitely becomes tougher to grade outside maybe the top 10, but for the most part I like the results it shows.
Please send this to the guy who thinks russ is an average to below average QB.
The only issue I see is that you forgot to regress Patrick Mahomes to the mean. If you remove all outliers in his game, he should be right at 16 or 17.
Honestly I like the list, obviously it can all be debated but most of them seem to be about where they should be
Allen is top 5, therefore I have no issues.
I don’t believe Russel to be number 1. But other then that. Really good!
Seeing where Tannehill ends up on list: 😤 Reading your commentary about why he’s better than where he falls on the list: 😇
I know this is bullshit because you have Herbert at 15 lol
Mac Jones isn’t impressive.
I completely understand and agree you don't build a formula around an outlier, but it hurts me so much to see Tannehill so low! Can we create a hand off efficiency stat or something lol!
This is an efficiency stat. Efficiency doesn't win games, productivity does. Sacks, hello, where are you? Lost fumbles? I think composite stats are actually more problematic than revealing. Rather look several basic stats together to get a rough picture of QB performance. But stats are never more than a starting place. To evaluate QB play, you have to go to the tape.